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KMID : 1240020230270000013
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International Neurourology Journal
2023 Volume.27 No. 0 p.13 ~ p.20
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Intravesical Bladder Treatment and Deep Learning Applications to Improve Irritative Voiding Symptoms Caused by Interstitial Cystitis: A Literature Review
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Cho Yong-Won
Youn Seung-Hyun
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Abstract
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Our comprehension of interstitial cystitis/painful bladder syndrome (IC/PBS) has evolved over time. The term painful bladder syndrome, preferred by the International Continence Society, is characterized as “a syndrome marked by suprapubic pain during bladder filling, alongside increased daytime and nighttime frequency, in the absence of any proven urinary infection or other pathology.” The diagnosis of IC/PBS primarily relies on symptoms of urgency/frequency and bladder/pelvic pain. The exact pathogenesis of IC/PBS remains a mystery, but it is postulated to be multifactorial. Theories range from bladder urothelial abnormalities, mast cell degranulation in the bladder, bladder inflammation, to altered bladder innervation. Therapeutic strategies encompass patient education, dietary and lifestyle modifications, medication, intravesical therapy, and surgical intervention. This article delves into the diagnosis, treatment, and prognosis prediction of IC/PBS, presenting the latest research findings, artificial intelligence technology applications in diagnosing major diseases in IC/PBS, and emerging treatment alternatives.
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KEYWORD
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Interstitial cystitis, Diagnosis, Treatment, Convolutional neural network, Deep learning
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